Visualization and Image Enhancement for Multistatic Underwater Laser Line Scan System Using Image-Based Rendering

Abstract

Over the last several decades, developments in underwater laser line scan (LLS) serial imaging sensors have resulted in significant improvements in turbid water imaging performance. In the last few years, there has been renewed interest in distributed, truly multistatic time-varying intensity (TVI) (i.e., multiple transmitter nonsynchronous LLS) sensor configurations. In addition to being capable of high-quality image acquisition through tens of beam attenuation lengths, while simultaneously establishing a non-line-of-sight free-space communications link, these system architectures also have the potential to provide a more synoptic image coverage of larger regions of seabed and the flexibility to simultaneously examine a target from different perspectives. A related issue worth investigation is how to utilize these capabilities to improve rendering of the underwater scenes. In this regard, light field rendering (LFR)-a type of image-based rendering (IBR) technique-offers several advantages. Compared to other IBR techniques, LFR can provide signal-to-noise ratio (SNR) improvements and the ability to image through obscuring objects in front of the target. On the other hand, multistatic nonsynchronous LLS can be readily configured to acquire image sequences needed to generate LFR. This paper investigates the application of LFR to images taken from a distributed bistatic nonsynchronous LLS imager using both line-ofsight and non-line-of-sight imaging geometries to create multiperspective rendering of an unknown underwater scene. The issues related to effectively applying this technique to underwater LLS imagery are analyzed and an image postprocessing flow to address these issues is proposed. The results from a series of experiments at the Harbor Branch Oceanographic Institute at the Florida Atlantic University (HBOI-FAU, Fort Pierce, FL, USA) optical imaging test tank demonstrated the capability of using bistatic/multistatic nonsynchronous LLS system to generated LFR and, therefore, verify the proposed image processing flow. The benefits of LFR to underwater imaging in challenging environments were further demonstrated via imaging against a variety of obstacles such as mesh screens, bubbles, and water at different turbidity. Image quality metrics based on mutual information and texture features were used in the analysis of the experimental results.